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Jingwei Zhang
Jingwei Zhang
DeepMind
Verified email at google.com
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Cited by
Cited by
Year
Deep reinforcement learning with successor features for navigation across similar environments
J Zhang, JT Springenberg, J Boedecker, W Burgard
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017
2822017
Socially compliant navigation through raw depth inputs with generative adversarial imitation learning
L Tai, J Zhang, M Liu, W Burgard
2018 IEEE international conference on robotics and automation (ICRA), 1111-1117, 2018
1962018
Neural slam: Learning to explore with external memory
J Zhang, L Tai, J Boedecker, W Burgard, M Liu
arXiv preprint arXiv:1706.09520, 2017
1712017
Vr-goggles for robots: Real-to-sim domain adaptation for visual control
J Zhang, L Tai, P Yun, Y Xiong, M Liu, J Boedecker, W Burgard
IEEE Robotics and Automation Letters 4 (2), 1148-1155, 2019
1202019
Curiosity-driven exploration for mapless navigation with deep reinforcement learning
O Zhelo, J Zhang, L Tai, M Liu, W Burgard
arXiv preprint arXiv:1804.00456, 2018
1052018
A survey of deep network solutions for learning control in robotics: From reinforcement to imitation
L Tai, J Zhang, M Liu, J Boedecker, W Burgard
arXiv preprint arXiv:1612.07139, 2016
952016
Deep reinforcement learning with successor features for navigation across similar environments. In 2017 IEEE
J Zhang, JT Springenberg, J Boedecker, W Burgard
RSJ International Conference on Intelligent Robots and Systems (IROS), 2371-2378, 0
37
Scheduled intrinsic drive: A hierarchical take on intrinsically motivated exploration
J Zhang, N Wetzel, N Dorka, J Boedecker, W Burgard
arXiv preprint arXiv:1903.07400, 2019
232019
Attend2Pack: Bin packing through deep reinforcement learning with attention
J Zhang, B Zi, X Ge
arXiv preprint arXiv:2107.04333, 2021
182021
A generalist dynamics model for control
I Schubert, J Zhang, J Bruce, S Bechtle, E Parisotto, M Riedmiller, ...
arXiv preprint arXiv:2305.10912, 2023
112023
Efficiency and equity are both essential: A generalized traffic signal controller with deep reinforcement learning
S Yan, J Zhang, D Büscher, W Burgard
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
102020
Perspectives on Deep Multimodel Robot Learning
W Burgard, A Valada, N Radwan, T Naseer, J Zhang, J Vertens, O Mees, ...
10*
Leveraging jumpy models for planning and fast learning in robotic domains
J Zhang, JT Springenberg, A Byravan, L Hasenclever, A Abdolmaleki, ...
arXiv preprint arXiv:2302.12617, 2023
42023
Supplement file of VR-Goggles for robots: Real-to-sim domain adaptation for visual control
J Zhang, L Tai, PYYXM Liu, JBW Burgard
Training 853 (840), 715, 2018
42018
Genie: Generative Interactive Environments
J Bruce, M Dennis, A Edwards, J Parker-Holder, Y Shi, E Hughes, M Lai, ...
arXiv preprint arXiv:2402.15391, 2024
32024
Offline Actor-Critic Reinforcement Learning Scales to Large Models
JT Springenberg, A Abdolmaleki, J Zhang, O Groth, M Bloesch, T Lampe, ...
arXiv preprint arXiv:2402.05546, 2024
12024
Equivariant data augmentation for generalization in offline reinforcement learning
C Pinneri, S Bechtle, M Wulfmeier, A Byravan, J Zhang, WF Whitney, ...
arXiv preprint arXiv:2309.07578, 2023
12023
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots
T Lampe, A Abdolmaleki, S Bechtle, SH Huang, JT Springenberg, ...
arXiv preprint arXiv:2312.11374, 2023
2023
pytorch-dnc
J Zhang
https://github.com/jingweiz/pytorch-dnc, 2017
2017
pytorch-rl
J Zhang, L Tai
https://github.com/jingweiz/pytorch-rl, 2017
2017
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Articles 1–20